Real-time dual-modal vein imaging system
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In this paper, we present a vein imaging system to combine reflectance mode visible spectrum images (VIS) with transmission mode near-infrared (NIR) images in real time. Clear vessel localization is achieved in this manner with combined NIR–VIS dual-modal imaging.
Transmission and reflectance mode optical instrumentation is used to combine VIS and NIR images. Two methods of displaying the combined images are demonstrated here. We have conducted experiments to determine the system’s resolution, alignment accuracy, and depth penetration. Vein counts were taken from the hands of test subjects using the system and compared with vein counts taken by visual analysis.
Results indicate that the system can improve vein detection in the human hand while detecting veins of a diameter < 0.5 mm at any working distance and of a 0.25 mm diameter at an optimal working distance of about 30 cm. The system has also been demonstrated to clearly detect silicone vessels with artificial blood of diameter 2, 1, and 0.5 mm diameter under a tissue depth of 3 mm. In a study involving 25 human subjects, we have demonstrated that vein visibility was significantly increased using our system.
The results indicate that the device is a high-resolution solution to near-surface venous imaging. This technology can be applied for IV placement, morphological analysis for disease state detection, and biometric analysis.
KeywordsNear-infrared Vein detection Optical imaging Computer vision
This study was supported in part by grants from the National Aeronautics and Space Administration (NASA Space Technology Research Fellowship NNX14AL37H), NSF Grant MCB-1616216, and the University of Akron Startup Funds.
Compliance with ethical standards
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study. Additional informed consent was obtained from all individual participants for whom identifying information is included in this article.
Demonstration video of how the system works in real time. It is intuitive and user-friendly (MP4 13971 kb)
- 2.Miyake RK, Zeman HD, Duarte FH, Kikuchi R, Ramacciotti E, Lovhoiden G, Vrancken C (2006) Vein imaging: a new method of near infrared imaging, where a processed image is projected onto the skin for the enhancement of vein treatment. Dermatol Surg 32(8):1031–1038. https://doi.org/10.1111/j.1524-4725.2006.32226.x Google Scholar
- 4.Fuksis R, Greitans M, Nikisins O, Pudzs M (2010) Infrared imaging system for analysis of blood vessel structure. Electron Electr Eng Kaunas Technol 97(1):45–48Google Scholar
- 5.Crisan S, Tarnovan JG, Crisan TE (2007) A low cost vein detection system using near infrared radiation. In: IEEE sensors applications symposium, San Diego, CA, USA. IEEE. https://doi.org/10.1109/SAS.2007.374359
- 6.Mansoor M, Sravani SN, Naqvi SZ, Badshah I, Saleem M (2013) Real-time low cast infrared vein imaging system. In: International conference on signal processing, image processing and pattern recognition, Coimbatore, India, 2013. IEEE. https://doi.org/10.1109/ICSIPR.2013.6497970
- 7.Paquita V, Pricea JR, Meriaudeaub F, Tobina KW, Ferrellc TL (2006) Combining near-infrared illuminants to optimize venous imaging. In: Medical imaging 2007: visualization and image-guided procedures, San Diego, CA, USA. SPIE, p 65090H. https://doi.org/10.1117/12.712576
- 8.Wang L, Leedham G (2006) Near- and far-infrared imaging for vein pattern biometrics. In: IEEE international conference on video and signal based surveillance, Sydney, NSW, Australia. IEEE. https://doi.org/10.1109/AVSS.2006.80
- 10.Michael GKO, Connie T, Teoh ABJ (2011) A contactless biometric system using palm print and palm vein features. In: Chetty G (ed) Advanced biometric technologies. InTech, pp 155–178. https://doi.org/10.1109/icarcv.2010.5707951
- 12.Cuper NJ, Klaessens JH, Jaspers JE, de Roodea R, Noordmans HJ, de Graaff JC, Verdaasdonk RM (2013) The use of near-infrared light for safe and effective visualization of subsurface blood vessels to facilitate blood withdrawal in children. Med Eng Phys 35:433–440. https://doi.org/10.1016/j.medengphy.2012.06.007 CrossRefGoogle Scholar
- 14.Francis M, Jose A, Devadhas G, Avinashe K (2017) A novel technique for forearm blood vein detection and enhancement. Biomed Res 28(7):2913–2919Google Scholar
- 17.Lee S, Park S, Lee D (2013) A phantom study on the propagation of NIR rays under the skin for designing a novel vein-visualizing device. In: 13th international conference on control, automation and systems, Gwangui, Korea. IEEE. https://doi.org/10.1109/ICCAS.2013.6704026
- 19.Newman A (1976) Photographic techniques in scientific research, vol 2. Academic Press, CambridgeGoogle Scholar
- 22.Kaddoum R, Anghelescu D, Parish M, Wright B, Trujillo L, Wu J, Wu Y, Burgoyne L (2012) A randomized controlled trial comparing the AccuVein AV300 device to standard insertion technique for intravenous cannulation of anesthetized children. Paediatr Anaesth 22(9):884–889. https://doi.org/10.1111/j.1460-9592.2012.03896.x CrossRefGoogle Scholar
- 24.Hebden JC, Alkhaja A, Mahe L, Powell S, Everdell N (2015) Measurement of contrast of phantom and in vivo subsurface blood vessels using two near-infrared imaging systems. In: Optical diagnostics and sensing XV: toward point-of-care diagnostics, San Francisco, CA, USA. SPIE, p 933213. https://doi.org/10.1117/12.2084673
- 27.Chen AI, Balter ML, Maguire TJ, Yarmush ML (2016) 3D near infrared and ultrasound imaging of peripheral blood vessels for real-time localization and needle guidance. In: Ourselin S, Joskowicz L, Sabuncu M, Unal G, Wells W (eds) Medical image computing and computer-assisted intervention, Athens, Greece. Lecture notes in computer science. Springer, pp 388–396. https://doi.org/10.1007/978-3-319-46726-9_45
- 28.Ahmed T, Rahman KS, Shawlin SS, Hasan M, Bhattacharjee A, Fattah SA, Shahnaz C (2017) Real time injecting device with automated robust vein detection using near infrared camera and live video. In: Global humanitarian technology conference (GHTC), San Jose, CA, USA. IEEE. https://doi.org/10.1109/GHTC.2017.8239298
- 33.Bandara A, Rajarata K, Giragama P (2017) Super-efficient spatially adaptive contrast enhancement algorithm for superficial vein imaging. In: IEEE international conference on industrial and information systems, Peradeniya, Sri Lanka. IEEE. https://doi.org/10.1109/iciinfs.2017.8300427
- 34.Yakno M, Saleh JM, Rosdi BA (2011) Low contrast hand vein image enhancement. In: IEEE international conference on signal and image processing applications, Kuala Lumpur, Malaysia. IEEE. https://doi.org/10.1109/ICSIPA.2011.6144135
- 37.Reza A (2004) Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement. J VLSI Signal Process Syst Signal Image Video Technol 38(1):35–44. https://doi.org/10.1023/B:VLSI.0000028532.53893.82 CrossRefGoogle Scholar